1. Field of the Invention
The invention relates generally to navigation systems and more particularly to a system and method of calibrating sensors in a navigation system utilizing dead-reckoning mechanisms in conjunction with GPS devices to determining the position of vehicles while the vehicle is traversing through areas of Global Positioning Satellite (GPS) signal outage.
2. Description of Related Art
It is often desirable to maintain location information on objects such as vehicles traveling through areas of partial or total GPS signal blockage or areas that present multi-path signals, or areas where external interferences cause GPS signal outage. Such areas may include urban canyons having natural and/or artificial structures causing partial or complete GPS signal blockage. For example, an airport location provides a challenge as there are generally numerous partial and total blockages due to overhead roadways, underground tunnels and densely populated artificial structures comprising the airport.
Typical navigation systems use dead-reckoning sensors to navigate through areas of partial or total GPS signal blockage. Dead-reckoning navigation systems utilize inertial measurements mechanisms, such as a flywheel, to provide navigation during partial signal outages. Sensors used in GPS-Dead-Reckoning (GPS-DR) systems include rate gyroscopes, magnetic heading sensors, accelerometers, odometers and differential odometers or wheel tick sensors. Automotive GPS applications suffer performance degradation when signals from the GPS satellites are blocked or reflected by local terrain, buildings, tunnels, and the vehicle itself. In certain applications, an automotive navigation system may still be required to provide an output even when the satellites are not visible. Use of a dead-reckoning system in these intervals is common practice. In particular, a GPS-DR system which uses a gyroscope to maintain heading and vehicle odometer input pulses to determine distance traveled is well known.
GPS and inertial sensor solutions provide a synergistic relationship when used together in hybrid navigation systems. The integration of these two types of solutions not only overcomes performance issues found in each individual solution, but produces a system whose performance exceeds that of the individual solutions. GPS provides bounded accuracy, while inertial system accuracy degrades with time.
In navigation systems, GPS receiver performance issues include susceptibility to interference from external sources, time to first fix, i.e., first position solution, interruption of the satellite signal due to blockage, integrity, and signal reacquisition capability. The performance issues related to inertial sensors are their associated quality and cost.
A primary concern with using GPS as a stand alone source for navigation is signal interruption. Signal interruption can be caused by shading of the GPS antenna by terrain or manmade structures, e.g., buildings, vehicle structure, and tunnels, or by interference from an external source. Generally, when only three usable satellite signals are available, most GPS receivers revert to a two-dimensional navigation mode by utilizing either the last known height or a height obtained from an external source. However, if the number of usable satellites is less than three, some receivers have the option of not producing a solution or extrapolating the last position and velocity solution forward in what is called xe2x80x9cdead-reckoningxe2x80x9d (DR) navigation. Position aiding from the inertial system can be used to help the GPS receiver reacquire the satellite signal. By sending vehicle position to the receiver, the receiver can accurately estimate the range from the given position to the satellites and thus initialize its internal code loops.
Generally, inertial sensors are of two typesxe2x80x94gyroscopes and accelerometers. The output of a gyroscope is a signal proportional to angular movement about its input axis and the output of an accelerometer is a signal proportional to the change in velocity sensed along its input axis. A three-axis inertial measurement unit (IMU) would then require three gyroscopes and three accelerometers to inertially determine its position and velocity in free space.
One of the significant factors related to the quality of an inertial system is the drift of the gyroscopes, measured in degrees/hour. The drift of a gyro is a false output signal caused by deficiencies during the manufacturing of the sensor. In inertial sensors, these are caused by mass unbalances in a gyroscope""s rotating mass and by non-linearities in the pickoff circuits as is seen in fiber-optic gyroscopes. This false signal is in effect telling the navigation system that the vehicle is moving when it is actually stationary. The manufacturing cost of gyros with low drift is approximately $1,000. An inertial unit with a drift from 1 to 100 deg/hr are currently priced from approximately $1,000 to $10,000. Inertial units providing accuracies of less than 1 deg/hr are available at prices significantly higher, ranging from ten to one hundred times the cost associated with lesser accurate units.
As can be seen, the quality of the inertial sensors has a large role in the cost effectiveness of a navigation system. If 0.0001-deg/hr gyroscopes were relatively inexpensive, GPS may not be needed today. However, in actuality, inertial sensors are expensive, and a significant result of the integration of GPS with inertial sensors is the ability to use lower performing, more cost-effective sensors. As mentioned above, during the operation of a navigation system when both GPS and inertial components are operational, the inertial navigation errors are bounded by the accuracy of the GPS solution. Thus, one significant contribution the GPS receiver makes to the operation of the inertial subsystem is the calibration of the inertial sensors. Inertial instruments are specified to meet a turn-on to turn-off drift requirement (each time a gyro is powered up, its initial drift rate differs.)
The major errors associated with inertial sensors used in conjunction with GPS systems (GPSI systems) are the gyro bias and accelerometer bias. The gyro bias and accelerometer bias typically occupy six of the states within an inertial or GPSI Kalman filter. During the operation of a GPSI system, the Kalman filter produces an estimate of these biases as derived from the velocity data received from the GPS receiver.
Integrated GPS systems, wherein GPS sensors are used in conjunction with inertial sensors (GPSI systems) have typically been accomplished by utilizing a single Kalman filter to estimate the navigation state and sensor errors. Kalman filtering is a statistical technique that combines a knowledge of the statistical nature of system errors with a knowledge of system dynamics, as represented as a state space model, to arrive at an estimate of the state of a system. In a navigation system, we are usually concerned with position and velocity, at a minimum, but its not unusual to see filters for system models with state vector dimensions ranging from six to sixty. The state estimate utilizes a weighting function, called the Kalman gain, which is optimized to produce a minimum error variance.
These designs have proven effective with high-quality inertial sensors but involve substantial costs. Unfortunately, increasing the Kalman filter state vector size involves substantial design time, tuning complexity, risk of numerical difficulties, and processing power costs. This often forces navigation designers into a harsh trade between estimating significant instrument errors and increasing state vector size.
Existing GPS-DR hybrid systems have evolved into several classes, switched and filtered. The switched and filtered GPS-DR hybrid systems are feed-forward designs which calibrate the instruments when GPS is available but do not use the dead-reckoning instruments to improve the operation of the GPS receiver.
Switched GPS-DR systems are simple and commonly available today. These systems are effective against a blockage, but do not offer increased resistance to multi-path or improved signal reacquisition. Switched GPS-DR systems typically use NMEA output from the GPS receiver and are therefore GPS vendor independent. The system switches between two states depending on the quality of the GPS solution. The two states include providing unaided GPS output or providing the dead-reckoning state propagated with the gyro and odometer. When the GPS solution quality is satisfactory the GPS velocity vector is used to update estimates of the odometer scale factor, heading, and gyro bias.
Filtered GPS-DR systems provide two independent navigation solutions, one based upon GPS and the other based upon DR sensors and/or map-matching information. The solutions are combined to produce a best solution for output or display. As in the switched system, the combined solution is not fed back to the GPS receiver to aid in rejecting multi-path or signal reacquisition. There are several map-matched implementations of this class of systems available today. In general map matching provides a path constraint which can be used to calibrate the DR sensors directly or to filter the GPS output before using the combined state to calibrate the sensors.
Hence, those concerned with improving efficient application of navigation systems while minimizing costs have recognized a need for a cost effective alternative to the single Kalman filter navigation system design. Furthermore, a need exists for an alternative to the switched and filtered GPS-DR design that provides a feed back of DR measurements to improve the solution of the GPS-DR solution. This invention fulfills those needs and others.
Briefly, and in general terms, the present invention relates to an integrated GPS-DR navigation system that uses dead-reckoning (DR) measurements to propagate the navigation states in the GPS receiver.
In a first aspect, the invention relates to a navigation system for tracking the position of an object. The navigation system includes a GPS receiver responsive to GPS signals for periodically providing navigation state measurement updates to a navigation processor. The system also includes a dead-reckoning sensor responsive to movement of the object for providing movement measurements to the navigation processor. The navigation processor determines object navigation states using the navigation state measurement updates and propagates the object navigation states between measurement updates using the movement measurements.
By utilizing the dead-reckoning sensors to propagate the GPS receiver""s navigation state between measurement updates, the present invention reduces the uncertainty, or process noise, associated with advancing the state from one measurement epoch to the next. The reduced uncertainties allow for a less noisy state estimation, a tighter constraint on measurements for rejection of multi-path, and improved reacquisition because of the availability of the dead-reckoned state to provide superior pre-positioning data.
In a detailed aspect, the navigation processor includes a navigation update unit that receives as input an updated dead-reckoning measurement and the navigation state measurement updates and provides as output navigation measurements and a modified dead-reckoning position measurement. The navigation update unit further includes a sensor update unit that receives as input the navigation measurements and the movement measurements and provides as output position changes. Also included in the navigation update unit is a navigation propagation unit that receives as input the position changes and the modified dead-reckoning measurement and provides as output the updated dead-reckoning measurement.
In a second aspect, the invention relates to a method of tracking the position of an object. The method includes periodically obtaining navigation state measurement updates and processing the navigation state measurement updates to determine object navigation states. The method also includes obtaining movement measurements related to object movement and propagating the object navigation states between measurement updates using the movement measurements.
In a third aspect, the invention relates to a navigation system for providing navigation information related to the movement of an object. The navigation system includes a global positioning satellite (GPS) receiver mounted to the object for receiving GPS signals and providing GPS measurements. The system further includes a navigation update unit that receives as input an updated dead-reckoning measurement and the GPS measurements and provides as output navigation measurements and a modified dead-reckoning position measurement. The system also includes at least one inertial sensor mounted to the object for sampling movement measurements and providing as output the movement measurements. Also included in the system in a sensor update unit that receives as input the navigation measurements and the movement measurements and provides as output position changes. The system also includes a navigation propagation unit that receives as input the position change and the modified dead-reckoning measurement and provides as output the updated dead-reckoning measurement.
In a detailed aspect of the invention, the navigation measurements include measurement changes in at least one of heading, gyro bias, gyro scale factor, speed bias, and speed scale factor. In another detailed facet of the invention, the sensor update unit includes a first processor for processing the changes in heading, gyro bias, and gyro scale factor along with the gyro measurement to produce a heading measurement and a second processor for processing the changes in speed bias and speed scale factor along with the speed measurement to produce changes in direction measurements. In another detailed aspect of the invention, the navigation update unit includes a first filter receiving as input the updated dead-reckoning measurement and the GPS measurements and providing as output an estimated velocity value, a second filter for estimating changes in heading, gyro bias, and gyro scale factor from first a measurement derived from the estimated velocity value and a third filter for estimating change in speed bias and speed scale factor from a second measurement derived from the estimated velocity value.
In its most basic form, the navigation system closely mimics the traditional single Kalman filter design by integrating separate GPS-navigation (first), heading (second) and speed (third) Kalman filters. This configuration makes up the federated filter architecture of the current invention. The federated filter architecture very nearly matches the single Kalman filter architecture thereby achieving the benefits of the single Kalman filter architecture at a substantially reduced throughput cost.
In a fourth aspect, the invention relates to a method of providing navigation information related to the movement of an object. The method includes receiving GPS signals by a global positioning satellite (GPS) receiver mounted to the object and providing as output GPS measurements. Also included is calculating navigation measurements and a modified dead-reckoning position measurement from an updated dead-reckoning measurement and the GPS measurements. Further included is the sampling of movement measurements by at least one inertial sensor mounted to the object, the processing of position changes from the navigation measurements and the movement measurements and the propagation of the updated dead-reckoning measurement calculated by the position change and the modified dead-reckoning measurement.
The navigation system is capable of calibrating the rate gyro bias, gyro scale factor, and odometer pulse scale factor and provides the advantage of continuous calibration of the sensor input data to provide accurate position solutions. One advantage of the system and method of the invention is the capability of using the dead-reckoning sensors in a feed back design to propagate the navigation state as they are calibrated. This continuous feed back propagation thereby reduces the process noise model in the primary navigation filter to take advantage of the reduced uncertainty in vehicle dynamics. The system further provides for adapting the measurement editing algorithm to take advantage of the reduced dynamic uncertainty allowing for tighter edit criteria to eliminate some multi-path corrupted measurements.
In a detailed aspect, the invention utilizes the last stored position, stored heading, the gyro and the odometer to generate a dead-reckoning navigation solution prior to the acquisition of GPS thereby providing a more efficient reacquisition solution. In another detailed aspect, the invention utilizes the zero turn-rate measurement to calibrate the gyro bias at start-up and allows for starting the heading sub-filter before the primary GPS filter starts to take advantage of the availability of the zero turn-rate measurement prior to the acquisition of GPS signals.
In a detailed facet of the invention, each individually integrated Kalman filter (KF), i.e., the primary navigation KF, heading KF, and speed KF, performs different estimation functions. The primary navigation KF is used as a position, velocity and clock state estimator. Although this filter is not substantially altered for adaptation in the present invention, there are modifications to the tuning parameters, changes to the process noise model, and changes in the moding logic and mechanisms to navigate with degraded constellations based on the availability of a dead-reckoning state. In another detailed aspect of the invention, the navigation system resets any of the three filters without resetting the other two thereby providing the advantage of continuous solution maintenance.
Furthermore, the system allows for estimating road grade from altitude changes when GPS is available, decaying the estimated road grade to zero after entering an outage with no GPS-based visibility of altitude, using the estimated road-grade to divide the odometer measured distance traveled into horizontal and vertical components for use in propagating the state-vector, and performing independent checks of the heading, speed, and primary Kalman filters against floors, ceilings, and correlation coefficient range limits.
These and other aspects and advantages of the invention will become apparent from the following detailed description and the accompanying drawings, which illustrate by way of example, the features of the invention.